feat: migrate semantic search to pgvector + full-text search

Replace JSON-string embeddings with native pgvector(1536) storage and
add PostgreSQL full-text search (tsvector/GIN) with Reciprocal Rank Fusion
for hybrid keyword + semantic ranking.

Changes:
- NoteEmbedding.embedding: String → vector(1536) via pgvector
- NoteEmbedding: added updatedAt for reindex tracking
- Note: added tsv (tsvector) with auto-update trigger for FTS
- semantic-search.service: hybrid FTS + vector search with RRF fusion
- embedding.service: toVectorString() for pgvector SQL literals
- Removed JS-side cosine similarity loops (now DB-side via <=>)
- Added HNSW index on NoteEmbedding.embedding (cosine distance)
- Added GIN index on Note.tsv for FTS queries

Schema migration in: prisma/migrations/20260512120000_pgvector_and_fts_search/

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

architectural-grid10/tsconfig.json

@@ -0,0 +1,26 @@
+{
+  "compilerOptions": {
+    "target": "ES2022",
+    "experimentalDecorators": true,
+    "useDefineForClassFields": false,
+    "module": "ESNext",
+    "lib": [
+      "ES2022",
+      "DOM",
+      "DOM.Iterable"
+    ],
+    "skipLibCheck": true,
+    "moduleResolution": "bundler",
+    "isolatedModules": true,
+    "moduleDetection": "force",
+    "allowJs": true,
+    "jsx": "react-jsx",
+    "paths": {
+      "@/*": [
+        "./*"
+      ]
+    },
+    "allowImportingTsExtensions": true,
+    "noEmit": true
+  }
+}